Increasing the robustness of channel estimates derived through sounding for WLAN

ABSTRACT

A plurality of training signal sets are transmitted. Each training signal set includes information sufficient to determine a channel estimate corresponding to a communication channel from a first station to a second station. A refined channel estimate is determined based on reception of the plurality of training signal sets.

CROSS-REFERENCE TO RELATED APPLICATIONS

The present application is a continuation application of U.S.application Ser. No. 12/186,437, now U.S. Pat. No. 8,095,097, entitled“INCREASING ROBUSTNESS OF CHANNEL ESTIMATES DERIVED THROUGH SOUNDING FORWLAN,” filed on Aug. 5, 2008, which claims the benefit of U.S.Provisional Patent Application No. 60/954,113, entitled “Increasing theRobustness of Channel Estimates Derived through Sounding for WLAN,”which was filed on Aug. 6, 2007. The disclosures of the above-referencedapplications are hereby incorporated by reference herein in theirentireties.

FIELD OF TECHNOLOGY

The present disclosure relates generally to wireless communicationsystems and, more particularly, to a system and method for estimating achannel in a wireless communication system with multiple transmitantennas and/or multiple receive antennas.

DESCRIPTION OF THE RELATED ART

An ever-increasing number of relatively inexpensive, low power wirelessdata communication services, networks and devices have been madeavailable over the past number of years, promising near wire speedtransmission and reliability. Various wireless technologies aredescribed in detail in the 802.11 IEEE Standard, including for example,the IEEE Standard 802.11 (1999) and its updates and amendments, the IEEEStandard 802.11a/g (2003), as well as the IEEE Standard 802.11n now inthe process of being adopted, all of which are collectively incorporatedherein fully by reference. These standards have been or are in theprocess of being commercialized with the promise of 54 Mbps or moreeffective bandwidth, making them a strong competitor to traditionalwired Ethernet and the more ubiquitous “802.11b” or “WiFi” 11 Mbpsmobile wireless transmission standard.

Generally speaking, transmission systems compliant with the IEEE 802.11aand 802.11g or “802.11a/g” as well as the 802.11n standards achievetheir high data transmission rates using Orthogonal Frequency DivisionModulation or OFDM encoded symbols mapped up to a 64 quadratureamplitude modulation (QAM) multi-carrier constellation. In a generalsense, the use of OFDM divides the overall system bandwidth into anumber of frequency sub-bands or channels, with each frequency sub-bandbeing associated with a respective sub-carrier upon which data may bemodulated. Thus, each frequency sub-band of the OFDM system may beviewed as an independent transmission channel within which to send data,thereby increasing the overall throughput or transmission rate of thecommunication system.

Transmitters used in the wireless communication systems that arecompliant with the aforementioned 802.11a/802.11g/802.11n standards aswell as other standards such as the 802.16a/d/e/m IEEE Standards,typically perform multi-carrier OFDM symbol encoding (which may includeerror correction encoding and interleaving), convert the encoded symbolsinto the time domain using Inverse Fast Fourier Transform (IFFT)techniques, and perform digital to analog conversion and conventionalradio frequency (RF) upconversion on the signals. These transmittersthen transmit the modulated and upconverted signals after appropriatepower amplification to one or more receivers, resulting in a relativelyhigh-speed time domain signal with a large peak-to-average ratio (PAR).

Likewise, the receivers used in the wireless communication systems thatare compliant with the aforementioned 802.11a/802.11g/802.11n and802.16a IEEE standards typically include an RF receiving unit thatperforms RF downconversion and filtering of the received signals (whichmay be performed in one or more stages), and a baseband processor unitthat processes the OFDM encoded symbols bearing the data of interest.The digital form of each OFDM symbol presented in the frequency domainis recovered after baseband downconversion, conventional analog todigital conversion and Fast Fourier Transformation of the received timedomain analog signal. Thereafter, the baseband processor performsfrequency domain equalization (FEQ) and demodulation to recover thetransmitted symbols, and these symbols are then processed in a Viterbidecoder to estimate or determine the most likely identity of thetransmitted symbol. The recovered and recognized stream of symbols isthen decoded, which may include deinterleaving and error correctionusing any of a number of known error correction techniques, to produce aset of recovered signals corresponding to the original signalstransmitted by the transmitter.

In wireless communication systems, the RF modulated signals generated bythe transmitter may reach a particular receiver via a number ofdifferent propagation paths, the characteristics of which typicallychange over time due to the phenomena of multi-path and fading.Moreover, the characteristics of a propagation channel differ or varybased on the frequency of propagation. To compensate for the timevarying, frequency selective nature of the propagation effects, andgenerally to enhance effective encoding and modulation in a wirelesscommunication system, each receiver of the wireless communication systemmay periodically develop or collect channel state information (CSI) foreach of the frequency channels, such as the channels associated witheach of the OFDM sub-bands discussed above. Generally speaking, CSI isinformation describing one or more characteristics of each of the OFDMchannels (for example, the gain, the phase and the SNR of each channel).Upon determining the CSI for one or more channels, the receiver may sendthis CSI back to the transmitter, which may use the CSI for each channelto precondition the signals transmitted using that channel so as tocompensate for the varying propagation effects of each of the channels.

An important part of a wireless communication system is therefore theselection of appropriate data rates, and the coding and modulationschemes to be used for a data transmission based on channel conditions.Generally speaking, it is desirable to use the selection process tomaximize throughput while meeting certain quality objectives, such asthose defined by a desired frame error rate (FER), symbol error rate,latency criteria, etc.

To further increase the number of signals which may be propagated in thecommunication system and/or to compensate for deleterious effectsassociated with the various propagation paths, and to thereby improvetransmission performance, it is known to use multiple transmit andreceive antennas within a wireless transmission system. Such a system iscommonly referred to as a multiple-input, multiple-output (MIMO)wireless transmission system and is specifically provided for within the802.11n IEEE Standard now being adopted. As is known, the use of MIMOtechnology produces significant increases in spectral efficiency andlink reliability, and these benefits generally increase as the number oftransmission and receive antennas within the MIMO system increases.

In addition to the frequency channels created by the use of OFDM, a MIMOchannel formed by the various transmit and receive antennas between aparticular transmitter and a particular receiver includes a number ofindependent spatial channels. As is known, a wireless MIMO communicationsystem can provide improved performance (e.g., increased transmissioncapacity) by utilizing the additional dimensionalities created by thesespatial channels for the transmission of additional data. Of course, thespatial channels of a wideband MIMO system may experience differentchannel conditions (e.g., different fading and multi-path effects)across the overall system bandwidth and may therefore achieve differentSNRs at different frequencies (i.e., at the different OFDM frequencysub-bands) of the overall system bandwidth. Consequently, the number ofinformation bits per modulation symbol (i.e., the data rate) that may betransmitted using the different frequency sub-bands of each spatialchannel for a particular level of performance may differ from frequencysub-band to frequency sub-band.

However, instead of using different transmit and receive antennas toform separate spatial channels on which additional information is sent,better reception properties can be obtained in a MIMO system by usingeach of the various transmit antennas of the MIMO system to transmit thesame signal while phasing (and amplifying) this signal as it is providedto the various transmit antennas to achieve beamforming or beamsteering.Generally speaking, beamforming or beamsteering creates a spatial gainpattern having one or more high gain lobes or beams (as compared to thegain obtained by an omni-directional antenna) in one or more particulardirections, while reducing the gain over that obtained by anomni-directional antenna in other directions. If the gain pattern isconfigured to produce a high gain lobe in the direction of each of thereceiver antennas, the MIMO system can obtain better receptionreliability between a particular transmitter and a particular receiver,over that obtained by single transmitter-antenna/receiver-antennasystems.

There are many known techniques for determining a steering matrixspecifying the beamsteering coefficients that need to be used toproperly condition the signals being applied to the various transmitantennas so as to produce the desired transmit gain pattern at thetransmitter. As is known, these coefficients may specify the gain andphasing of the signals to be provided to the transmit antennas toproduce high gain lobes in particular or predetermined directions. Thesetechniques include, for example, transmit-MRC (maximum ratio combining)and singular value decomposition (SVD). An important part of determiningthe steering matrix is taking into account the specifics of the channelbetween the transmitter and the receiver, referred to herein as theforward channel. As a result, steering matrixes are typically determinedbased on the CSI of the forward channel. However, to determine the CSIor other specifics of the forward channel, the transmitter must firstsend a known test or calibration signal to the receiver, which thencomputes or determines the specifics of the forward channel (e.g., theCSI for the forward channel) and then sends the CSI or other indicationsof the forward channel back to the transmitter, thereby requiringsignals to be sent both from the transmitter to the receiver and thenfrom the receiver back to the transmitter in order to performbeamforming in the forward channel. Moreover, this exchange must occureach time the forward channel is determined (e.g., each time a steeringmatrix is to be calculated for the forward channel).

To reduce the amount of startup exchanges required to performbeamforming based on CSI or other channel information, it is known toperform implicit beamforming in a MIMO communication system. Withimplicit beamforming, the steering matrix is calculated or determinedbased on the assumption that the forward channel (i.e., the channel fromthe transmitter to the receiver in which beamforming is to beaccomplished) can be estimated from the reverse channel (i.e., thechannel from the receiver to the transmitter). In particular, theforward channel can ideally be estimated as the matrix transpose of thereverse channel. Thus, in the ideal case, the transmitter only needs toreceive signals from the receiver to produce a steering matrix for theforward channel, as the transmitter can use the signals from thereceiver to determine the reverse channel, and can simply estimate theforward channel as a matrix transpose of the reverse channel. As aresult, implicit beamforming reduces the amount of startup exchangesignals that need to be sent between a transmitter and a receiverbecause the transmitter can estimate the forward channel based solely onsignals sent from the receiver to the transmitter. Additionally, U.S.patent application Ser. No. 11/857,297, filed on Sep. 18, 2007, andentitled “Calibration Correction for Implicit Beamforming in a WirelessMIMO Communication System,” which is hereby incorporated by referenceherein, describes techniques for improving the performance of implicitbeamforming by calculating and utilizing correction matrices that canapplied to the signal to be transmitted via the forward channel or thatcan be applied to the steering matrix, for example.

SUMMARY

In one embodiment, a method includes causing a plurality of trainingsignal sets to be transmitted, and receiving the plurality of trainingsignal sets, wherein each received training signal set includesinformation sufficient to determine a channel estimate corresponding toa communication channel from a first station to a second station. Themethod also includes determining a refined channel estimate based on theplurality of received training signal sets.

In another embodiment, a method includes receiving a plurality oftraining signal sets from a first station, wherein each receivedtraining signal set includes information sufficient to determine achannel estimate corresponding to a communication channel from the firststation to a second station. Additionally, the method includesdetermining a refined channel estimate corresponding to thecommunication channel from the first station to the second station basedon the plurality of received training signal sets.

In yet another embodiment, a method includes transmitting a plurality oftraining signal sets to a first station, wherein each training signalset includes information sufficient for determining a channel estimatecorresponding to a communication channel from a second station to thefirst station. Also, the method includes receiving respective individualchannel estimates from the first station in response to each of theplurality of training signal sets, and determining a refined channelestimate corresponding to the communication channel from the secondstation to the first station based on the plurality of individualchannel estimates.

In still another embodiment, a wireless transceiver comprises aplurality of antennas, a pre-coding processor coupled to the pluralityof antennas, and a modulation unit coupled to the pre-coding processor.The wireless transceiver also comprises a controller coupled to themodulation unit to cause a plurality of training signal sets to betransmitted, wherein each training signal set includes informationsufficient to determine a channel estimate corresponding to acommunication channel. The wireless transceiver additionally comprises achannel determination unit to generate a refined channel estimate basedon channel state information determined based on transmission of theplurality of training signal sets.

In yet another embodiment, a first wireless transceiver comprises aplurality of antennas, a pre-coding processor coupled to the pluralityof antennas, and a modulation unit coupled to the pre-coding processor.Additionally, the first wireless transceiver comprises a channeldetermination unit to generate a refined channel estimate based on aplurality of received training signal sets received from a secondwireless transceiver, wherein each received training signal set includesinformation sufficient to determine a channel estimate corresponding toa communication channel from the second wireless transceiver to thefirst wireless transceiver.

In another embodiment, a first wireless transceiver comprises aplurality of antennas, a pre-coding processor coupled to the pluralityof antennas, and a modulation unit coupled to the pre-coding processor.Also, the first wireless transceiver comprises a controller coupled tothe modulation unit to cause a plurality of training signal sets to betransmitted from the first wireless transceiver to a second wirelesstransceiver, wherein each training signal set includes informationsufficient to determine a channel estimate corresponding to acommunication channel from the first wireless transceiver to a secondwireless transceiver. The first wireless transceiver additionallycomprises a channel determination unit to generate a refined channelestimate based on a plurality of respective individual channel estimatesreceived from the second wireless transceiver in response to each of theplurality of training signal sets.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 is a block diagram of a wireless MIMO communication ortransmission system that may implement channel estimation techniquessuch as described herein;

FIG. 2 is a block diagram illustrating a transmit gain pattern forwireless communications between a single transmitter and a singlereceiver;

FIG. 3 is a block diagram illustrating a transmit gain pattern forwireless communications between a single transmitter and multiplereceivers;

FIG. 4 is a flow diagram of an example channel estimation method;

FIG. 5A is a block diagram of a high definition television that mayutilize channel estimation techniques such as described herein;

FIG. 5B is a block diagram of a vehicle that may utilize channelestimation techniques such as described herein;

FIG. 5C is a block diagram of a cellular phone that may utilize channelestimation techniques such as described herein;

FIG. 5D is a block diagram of a set top box that may utilize channelestimation techniques such as described herein;

FIG. 5E is a block diagram of a media player that may utilize channelestimation techniques such as described herein; and

FIG. 5F is a block diagram of a voice over IP device that may utilizechannel estimation techniques such as described herein.

DETAILED DESCRIPTION

While some of the channel estimation techniques described herein forprocessing and effecting a wireless data transmission are described asbeing used in communication systems that use the IEEE Standard 802.11ncommunication standard, these techniques may be used in various othertypes of wireless communication systems and are not limited to thoseconforming to the IEEE Standard 802.11n standard. For example, thechannel estimation techniques may be utilized in communication systemsconforming to one of the other IEEE 802.11x standards, the IEEE 802.16standards, Release 8 of the Third Generation Partnership Project (3GPP)specification, proprietary communication systems, etc. As otherexamples, the channel estimation techniques may be utilized in singleinput, multiple output (SIMO) and multiple input, single output (MISO)communication systems, in communication systems in which a modulationscheme other than OFDM is utilized, etc.

Referring now to FIG. 1, a MIMO communication system 10 is illustratedin block diagram form as generally including a single transceiver device12 (hereinafter referred to as transmitter 12) having multiple transmitantennas 14A-14N and a single transceiver device 16 (hereinafterreferred to as receiver 16) having multiple receiver antennas 18A-18M.The number of transmit antennas 14A-14N can be the same as, more than,or less than the number of receiver antennas 18A-18M. As shown in FIG.1, the transmitter 12 may include a controller 20 coupled to a memory21, a symbol encoder and modulator unit 22 and a space-time filtering ormapping block 24, also referred to herein as a transmit beamformingnetwork. The transmitter 12 may also include a matrix equalizer 25 and asymbol demodulator and decoder unit 26 to perform demodulation anddecoding of signals received via the antennas 14A-14N in a receive mode.Additionally, the transmitter 12 includes a channel determination unit27 and a steering matrix calculation unit 28. The controller 12 may beany desired type of controller, and the controller 12, the channeldetermination unit 27 and the steering matrix calculation unit 28 may beimplemented as one or more standard multi-purpose, programmableprocessors, such as micro-processors, as application specific integratedcircuits (ASICs), etc., or may be implemented using any other desiredtypes of hardware, software and/or firmware. Likewise, the pre-codingblock 24 or beamforming network, and the matrix equalizer 25 may beimplemented using known or standard hardware and/or software elements.If desired, various of the transmitter components, such as thecontroller 20, the modulator unit 22, the demodulator unit 26, thechannel determination unit 27, the steering matrix calculation unit 28,the precoding block 24 and the matrix equalizer 25 may be implemented inthe same or in different hardware devices, such as in the same ordifferent processors. Additionally, each of these components of thetransmitter 12 may be disposed in a housing 29 (shown in dotted reliefin FIG. 1). Still further, the routines or instructions for implementingthe functionality of any of these components may be stored in the memory21 or within other memory devices associated with the individualhardware used to implement these components.

During operation, information signals T_(x1)-T_(xn) which are to betransmitted from the transmitter 12 to the receiver 16 are provided tothe symbol encoder and modulator unit 22 for encoding and modulation. Ofcourse, any desired number of signals T_(x1)-T_(xn) may be provided tothe modulator unit 22, with this number generally being limited by themodulation scheme used by and the bandwidth associated with the MIMOcommunication system 10. Additionally, the signals T_(x1)-T_(xn) may beany type of signals, including analog or digital signals, and mayrepresent any desired type of data or information. Additionally, ifexplicit channel estimation is utilized, a known training signal C_(x1)(which may be stored in the memory 21) may be provided to the symbolencoder and modulator unit 22 for use in determining CSI relatedinformation describing the characteristics of the channel from thetransmitter 12 to the receiver 16. The same training signal or adifferent training signal may be used to determine the CSI for eachfrequency and/or spatial channel used in the MIMO communication system10. Thus, a set of training signals may be transmitted from thetransmitter 12 to the receiver 16 in order to determine the CSI for theforward channel from the transmitter 12 to the receiver 16, and the setof training signals may include information sufficient for determiningthe CSI for the forward channel. For a MIMO channel corresponding to mreceive antennas and n transmit antennas, the CSI may be afull-dimensional description of the channel (i.e., providing an m-by-ndescription of the channel), or a partial-dimensional description of thechannel (i.e., providing a p-by-q description of the channel, where p<mand/or q<n). The set of training signals may be included in a packetsuch as a sounding packet, a null data packet, etc.

The symbol encoder and modulator unit 22 may interleave digitalrepresentations of the various signals T_(x1)-T_(xn) and C_(x1) and mayperform any other known type(s) of error-correction encoding on thesignals T_(x1)-T_(xn) and C_(x1) to produce one or more streams ofsymbols to be modulated and sent from the transmitter 12 to the receiver16. While the symbols may be modulated using any desired or suitable QAMtechnique, such as using 64 QAM, these symbols may be modulated in anyother known or desired manner including, for example, using any otherdesired phase and/or frequency modulation techniques. In any event, themodulated symbol streams are provided by the symbol encoder andmodulator unit 22 to the pre-coding block 24 for processing before beingtransmitted via the antennas 14A-14N. While not specifically shown inFIG. 1, the modulated symbol streams may be up-converted to the RFcarrier frequencies associated with an OFDM technique (in one or morestages) before being processed by the space-time mapping block 24 inaccordance with a beamforming technique more specifically describedherein. Upon receiving the modulated signals, the pre-coding block 24 orbeamforming network processes the modulated signals by injecting delaysand/or gains into the modulated signals based on a steering matrixprovided by the controller 12, to thereby perform beamsteering orbeamforming via the transmit antennas 14A-14N.

The signals transmitted by the transmitter 12 are received by thereceiver antennas 18A-18M and may be processed by a matrix equalizer 35within the receiver 16 to enhance the reception capabilities of theantennas 18A-18M. As will be understood, the processing applied at thereceiver 16 (as well as at the transmitter 12) may be based on, forexample, the CSI developed by the receiver 16 in response to the set oftraining signals transmitted by the transmitter 12. In particular, acontroller 40 or other unit within the receiver 16, such as a channeldetermination unit 39, may process the received set of training signalsand develop therefrom a measured description of the forward channelbetween the transmitter 12 and the receiver 16 by determining orcharacterizing the propagation effects of the forward channel on the setof training signals as it traveled through the forward channel. Ifexplicit channel estimation is utilized, the CSI determined by thereceiver 16 is transmitted back to the transmitter 12. The transmitter12 may then utilize the CSI for the forward channel, determined by thereceiver 14, for beamforming calculations, modulation coding set (MCS)selection, etc. In any event, a symbol demodulator and decoder unit 36,under control of the controller 40, may decode and demodulate thereceived symbol strings as processed by the matrix equalizer 35. In thisprocess, these signals may be downconverted to baseband. Generally, thedemodulator and decoder unit 36 may operate to remove effects of theforward channel based on the CSI as well as to perform demodulation onthe received symbols to produce a digital bit stream. In some cases, ifdesired, the symbol demodulator and decoder unit 36 may perform errorcorrection decoding and deinterleaving on the bit stream to produce thereceived signals R_(x1)-R_(xn) corresponding to the originallytransmitted signals T_(x1)-T_(xn).

As shown in FIG. 1, the receiver 16 may also include a memory 41 and asymbol encoder and modulator unit 46 which may receive one or moresignals T_(R1)-T_(Rm) which may be encoded and modulated using anydesired encoding and modulation techniques. The receiver 16 may alsoprovide one or more known test or control signals C_(R1) to the symbolencoder/modulator unit 46 to be sent to the transmitter 12 to enable thetransmitter 12 to determine a measured description of the reversechannel from the receiver 16 to the transmitter 12. Similar to thetraining signals transmitted by the transmitter 12, a set of trainingsignals may be transmitted from the receiver 16 to the transmitter 12 inorder to determine the CSI for the reverse channel, and the set oftraining signals may include information sufficient for determining theCSI for the reverse channel. For a MIMO channel corresponding to mreceive antennas and n transmit antennas, the CSI may be afull-dimensional description of the channel or a partial-dimensionaldescription of the channel. The set of training signals may be includedin a packet such as a sounding packet, a null data packet, etc.

The encoded and modulated symbol stream may then be upconverted andprocessed by a pre-coding block 34 to perform beamsteering based on asteering matrix developed by a steering matrix calculation unit 48,prior to being transmitted via the receiver antennas 18A-18N to, forexample, the transmitter 12, thereby implementing the reverse link. Asshown in FIG. 1, each of the receiver components may be disposed in ahousing 51.

The matrix equalizer 25 and the demodulator/decoder unit 26 within thetransmitter 12 operate similarly to the matrix equalizer 35 and thedemodulator/decoder unit 36 of the receiver 16 to demodulate and decodethe signals transmitted by the receiver 16 to produce the recoveredsignals R_(R1)-R_(Rm). Here again, the matrix equalizer 25 may processthe received signals in any known manner to enhance the separation andtherefore the reception of the various signals transmitted by theantennas 18A-18M. Of course, the CSI or other measured description ofthe forward channel for the various OFDM channel(s) may be used by thesteering matrix calculation units 28 and 48 as well as by thecontrollers 20 and 40 to perform beamforming and to determine a steeringmatrix used by the pre-coding blocks 24, 34. Additionally, the CSI orother measured description of the forward channel for the various OFDMchannel(s) may be used by the controllers 20 and 40 and/or themodulators 22, 46 to perform MCS selection. As noted above, the CSI,beamforming and other programs and data such as the steering matrix usedby the units 28 and 48 and by the controllers 20 and 40, a selected MCS,etc. may be stored in the memories 21 and 41.

If implicit channel estimation is utilized, the CSI for the forwardchannel may be developed by the transmitter 12 in response to areception of the set of training signals sent by the receiver 16. Inparticular, the controller 20 or other unit within the transmitter 12,such as a channel determination unit 27, may process the set of trainingsignals received from the receiver 16 and develop therefrom a measureddescription of the reverse channel from the receiver 16 to thetransmitter 12 by determining or characterizing the propagation effectsof the reverse channel on the set of training signals as it traveledthrough the reverse channel. Then, the CSI of the forward channel may beestimated based on the determined CSI for the reverse channel and/or theforward channel estimate can be estimated based on a reverse channelestimate. For example, a forward channel estimate matrix may bedetermined as the matrix transpose of a reverse channel matrix. Thus, inthe ideal case, the transmitter only needs to receive signals from thereceiver to produce a steering matrix for the forward channel, as thetransmitter can use the signals from the receiver to determine thereverse channel, and can simply estimate the forward channel as a matrixtranspose of the reverse channel. As a result, implicit beamformingreduces the amount of startup exchange signals that need to be sentbetween a transmitter and a receiver because the transmitter canestimate the forward channel based solely on signals sent from thereceiver to the transmitter. Optionally, a correction matrix can becalculated that can applied to the signal to be transmitted via theforward channel or that can be applied to the steering matrix, forexample, as described in U.S. patent application Ser. No. 11/857,297.Such correction matrices may improve the forward channel estimate and/orforward channel beamforming when implicit channel estimation isutilized. Similarly, the CSI for the reverse channel may be developed bythe receiver 16 in response to a reception of the set of trainingsignals sent by the transmitter 12. In particular, the controller 40 orother unit within the receiver 16, such as a channel determination unit39, may process the set of training signals received from thetransmitter 12 and develop therefrom a measured description of theforward channel from the transmitter 12 to the receiver 16 bydetermining or characterizing the propagation effects of the forwardchannel on the set of training signals as it traveled through theforward channel. Then, the CSI of the reverse channel may be estimatedbased on the determined CSI for the forward channel and/or the reversechannel estimate can be estimated based on a forward channel estimate.

As is generally known, beamforming or beamsteering typically includesapplying appropriate phases and gains to the various signals as sentthrough the multiple transmit antennas 14A-14N, in a manner which causesthe signals sent from the different transmit antennas 14A-14N toconstructively interact (add in phase) in certain predetermineddirections and to deconstructively interact (cancel) in otherdirections. Thus, beamsteering typically produces a beam pattern havinghigh gain regions (referred to as high gain lobes) in variouspredetermined directions and low gain regions (typically referred to asnulls) in other directions. The use of beamforming techniques in a MIMOsystem enables a signal to be sent with high gain (as compared to anomni-directional antenna) in certain directions, and to be sent with lowgain (as compared to an omni-directional antenna) in other directions.Thus, in the MIMO system 10 of FIG. 1, beamforming may be used toenhance signal directivity towards the receive antennas 18A-18M, whichimproves the SNR of the transmissions and results in more reliabletransmissions. In this case, the beamforming technique will generallyform high gain lobes in the direction of propagation at which thehighest gain is desired, and in particular in the directions ofpropagation from the transmitter 12 to each of the receive antennas18A-18M of the receiver 16 or to the receiver 16 in general.

To implement beamforming in the transmitter 12, the steering matrixcalculation unit 28 may determine or calculate a set of matrixcoefficients (referred to herein as a steering matrix) which are used bythe space-time mapping block or beamforming network 24 to condition thesignals being transmitted by the antennas 14A-14N. Generally speaking,the steering matrix for any particular frequency channel of the MIMOsystem 10 (in the forward channel between the transmitter 12 and thereceiver 16) may be determined by the steering matrix calculation unit28 based on the CSI determined for that forward channel. In this case,the steering matrix calculation unit 28 may use any desired beamsteering or matrix computation techniques, such as transmit-MRC or SVDtechniques, to compute the steering matrix. As these techniques are wellknown in the art, they will not be discussed in detail herein.

However, as is known, to actually determine the CSI or other measureddescription of the forward channel, i.e., for the channel from thetransmitter 12 to the receiver 16, the transmitter 12 generally sendsthe set of training signals (e.g., including the signal C_(x1)) and thereceiver 16 may then determine the CSI or other measured description ofthe forward channel and send this information back to the transmitter 12as part of a payload of a transmission. In the event of explicitbeamforming, in this case, the transmitter 12 must first send the set oftraining signals to the receiver 16 which then determines a measureddescription of the forward channel and sends this description of theforward channel from the receiver 16 back to the transmitter 12. Thischaracterization of the forward channel thereby requires, each time thesteering matrix is computed, multiple communications between thetransmitter 12 and the receiver 16 so as to enable the transmitter 12 toobtain the CSI or other description of the forward channel used todevelop the steering matrix to be used in the forward channel. In thecase of implicit beamforming, to avoid the use of multiple communicationbetween a particular transmitter/receiver pair each time a steeringmatrix is to be computed for the forward channel, the transmitter 12 maydetermine the CSI or other measured description of the reverse channel,i.e., the channel from the receiver 16 to the transmitter 12, from theset of training signals sent from the receiver 16 including, for examplethe known test or control signal C_(R1). Based on the CSI or othermeasured description of the reverse channel, the transmitter 12 maycalculate the steering matrix for the forward channel.

To reduce or account for the errors introduced by RF chain impairmentsin a standard implicit beamforming technique, the transmitter 12optionally may use a calibration technique that applies a correctionmatrix during the beamforming process to compensate for measureddifferences between the actual forward and reverse channels. Thistechnique is described in U.S. patent application Ser. No. 11/857,297.In particular, this technique first determines a correction matrix as afunction of measured descriptions of the forward and the reversechannels. Then, each time a new steering matrix is to be calculated forthe forward channel, the beamforming technique applies the correctionmatrix to a steering matrix determined using a basic implicitbeamforming technique, so that, once the correction matrix isdetermined, the transmitter may simply perform implicit beamformingusing a measured description of the reverse channel (i.e., the channelbetween the receiver and the transmitter) to produce an estimate of theforward channel (i.e., the channel between the transmitter and thereceiver). Alternatively, the transmitter 12 may also calculatecorrection matrices for its receive chains, so that once the correctionmatrix is determined, the transmitter may apply it to the reversechannel (i.e., the channel from the receiver 16 to the transmitter 12)estimation, and perform implicit beamforming using a measureddescription of this processed reverse channel estimate to produce anestimate of the forward channel (i.e., the channel from the transmitter12 to the receiver 16). The calibration procedure may be conductedinfrequently, compared with steering matrix updates. For example, it maybe conducted only upon association of the device into the network, orupon the changes in the environment (e.g. a change in temperature).

As the SNR of the channel decreases (such as when the distance betweenthe transmitter 12 and the receiver 16 increases), the determined CSImay provide a less accurate characterization of the channel, leading toless accurate channel estimates. Because the steering matrix (and othertransmitter functions such as MCS selection) is determined based on thechannel estimate, the determined steering matrix (or MCS selection) maybe flawed or sub-optimal if a low SNR resulted in a poor channelestimate. Channel estimate techniques are described subsequently thatenable the calculation of more accurate channel estimates when SNR islow, such as when the distance between the transmitter 12 and thereceiver 16 is high relative to the transmit power of the transmitter12.

To illustrate beamforming scenarios with which the channel estimatetechniques described below can be utilized, FIG. 2 shows a MIMOcommunication system 110 having a single transmitter 112 with sixtransmitter antennas 114A-114F, and a single receiver 116 with fourreceiver antennas 118A-118D. In this example, the steering matrix may bedeveloped by the transmitter 112 using feedback indicative of the CSI tocreate a transmit gain pattern 119 as shown disposed next to thetransmitter 112. As illustrated in FIG. 2, the transmit gain pattern 119includes multiple high gain lobes 119A-119D disposed in the directionsof the receiver antennas 118A-118D. The high gain lobes 119A-119D areorientated in the directions of propagation from the transmitter 112 tothe particular receiver antennas 118A-118D while lower gain regions,which may even include one or more nulls, are produced in otherdirections of propagation. While FIG. 2 illustrates a separate high gainlobe directed to each of the receiver antennas 118A-118D, it will beunderstood that the actual gain pattern produced by the beam steeringmatrix calculations using information pertaining to the matrix equalizerof the receiver 116 may not necessarily include a separate high gainlobe for each of the receiver antennas 118A-118D. Instead, the gainpattern developed by the beam steering matrix for the transmitter 112may have a single high gain lobe covering or directed generally to morethan one of the receiver antennas 118A-118D. Thus, it is to beunderstood that the beam pattern resulting from the creation of asteering matrix may or may not have separate high gain lobes separatedby low gain regions or nulls for each of the receiver antennas.

Of course, developing the beam pattern 119 to have high gain regions andlow gain regions may be performed in any desired manner and location.For example, any of the components within the receiver 16 of FIG. 1,including the controller 40 and the steering matrix calculation unit 48optionally may process steering information and may then send thisinformation to the transmitter 12. In this case, the controller 20 orthe steering matrix calculation unit 28 within the transmitter 12 mayuse the steering information to determine the steering matrix for use inthe precoding block 24 for performing beamforming to the receiver 16. Onthe other hand, the controller 40 or the steering matrix calculationunit 48 within the receiver 16 may use the steering information todetermine the steering matrix for use in the precoding block 24 of thetransmitter 12, and may then transmit this steering matrix to thetransmitter 12.

The receiver 116 may compute the steering matrix to be used by thetransmitter 112 based on the CSI developed by the receiver 116, and maysend the actual steering matrix to the transmitter 112 to be used intransmitting information to the receiver 16. On the other hand, thesteering matrix for the transmitter precoding block 24 of FIG. 1 may becalculated by the steering matrix calculation unit 28 within thetransmitter 12 based on the CSI provided and sent back from the receiver16 to the transmitter 12. With implicit beamforming, the steering matrixfor the transmitter precoding block 24 of FIG. 1 may be calculated bythe steering matrix calculation unit 28 within the transmitter 12 basedon CSI for the reverse channel.

Of course, the channel estimate techniques described herein are notlimited to being used with a transmitter of a MIMO communication systemcommunicating with a single receiver of the MIMO communication system,but can additionally be applied when a transmitter of a MIMOcommunication system is communicating with multiple receivers, each ofwhich has one or more receiver antennas associated therewith. Forexample, FIG. 3 illustrates a MIMO system 210 in which a singletransmitter 212 having multiple (in this example six) transmitterantennas 214A-214F transmits to multiple receivers 216, 218, 220 and222, each having multiple receiver antennas 226A-226C, 228A-228C,230A-230D, and 232A-232D, respectively. While shown in this example asincluding three or four receiver antenna, any or all of the receivers216, 218, 220, 222 of FIG. 3 could include different numbers of receiverantennas, including only a single receiver antenna if so desired. In anyevent, as illustrated by the transmit gain pattern 240 illustrated inFIG. 3, the steering matrix calculated and used by the transmitter 212is formed using steering information and/or CSI generated by one or moreof the transmitter 212 and/or the receivers 216, 218, 220 and 222.

In one example, the transmitter steering matrix may be calculated ordetermined using steering information or CSI generated by each of thereceivers 216, 218, 220 and 222, so that, as shown by the transmit gainpattern 240, a high gain lobe is directed to at least one receiverantenna of each of the receivers 216, 218, 220, 222 at the same time.However, the steering matrix need not necessarily produce a high gainlobe directed to all of the receiver antennas of each of the receivers216, 218, 220, 222, and not necessarily to all of the receiver antennasfor any particular one of the receivers 216, 218, 220, 222. Thus, asillustrated in FIG. 3, the steering matrix for the transmitter 212 isdetermined in such a manner that a separate high gain lobe is directedto each of the receiver antennas 226A, 226B, 226C, 228A, 228C, 230A,230B and 230D. However, due to the physical location of the receiver 222and its antennas with respect to the transmitter 212, a single high gainlobe is directed to the receiver antennas 232A-232D, resulting in asingle high gain lobe in the transmit gain pattern 240 directed to allof these receiver antennas

On the other hand, the transmitter 212 may develop a different steeringmatrix for each of the receivers 216, 218, 220 and 222 using steeringinformation and/or CSI generated by each of these receivers, and may usethose steering matrixes to beamform to the separate or differentreceivers at different times or using different channels, e.g., OFDMchannels, of the system.

While, in many cases, it will be desirable to beamform in such a way todirect a high gain lobe to at least one receiver antenna from eachreceiver, it may not be necessary to implement this requirement in allcases. For example, a particular receiver may be in a direct line ofsight from the transmitter to another receiver and therefore may bedisposed in a high gain region of the transmitter and may thusadequately receive the transmitted signals from the transmitter withoututilizing steering information or CSI generated by that receiver. Asanother example, a particular receiver may be disposed in a low gainregion associated with the transmitter, but may be disposed relativelyclose to the transmitter so that the particular receiver adequatelyreceives the signals transmitted by the transmitter without utilizingsteering information generated by that receiver. Of course, if desired,the number and location (identity) of the receivers used in calculatingthe transmitter steering matrix can be determined in any manner,including by trial and error, in determining an acceptable or optimalsteering matrix using steering information generated by more than onereceiver. Still further, while the maximum gains of the high gain lobesof each of the transmit gain patterns shown in FIGS. 2 and 3 are shownas being the same, the steering matrix calculation units 28 and 48 maydevelop steering matrixes which produce high gain lobes with differingmaximum gains.

If implicit beamforming is utilized, the transmitter 212 may developsteering matrices based on CSI associated with the multiple reversechannels between the transmitter 212 and the multiple receivers 216,218, 220 and 222.

FIG. 4 is a block diagram of an example method 250 for generating achannel estimate. The channel estimate may be utilized for varioustransmitter processing functions such as calculating a steering matrix,MCS selection, etc. The method 250 will be described with reference toFIG. 1 for explanatory purposes. It will be understood, however, thatthe method 250 may be utilized with systems other than the system 10 ofFIG. 1.

At block 254, a signal-to-noise ratio (SNR) of a channel may bedetermined. The SNR of the channel may be determined in a variety ofways, including using currently known techniques. For example, the SNRfor a channel may be determined based on, or included in, the CSI forthe channel. As discussed above, the CSI for a channel may be determinedbased on transmitting a training signal set and receiving the trainingsignal set. Thus, for explicit beamforming and/or explicit channelestimation corresponding to a forward channel, the transmitter maytransmit the training signal set to the receiver 16. Then, the CSI forthe forward channel may be determined by the receiver 16, and thereceiver 16 may transmit the CSI back to the transmitter 12. Thetransmitter 12 may then determine the SNR based on the CSI. Optionally,if the SNR is not already included in the CSI, the SNR for the forwardchannel may be determined by the receiver 16, and then the receiver 16may transmit the determined SNR back to the transmitter 12. For implicitbeamforming and/or implicit channel estimation corresponding to aforward channel, the CSI for the forward channel may be determined bythe transmitter 12 based on CSI of the reverse channel. For example, thetransmitter 12 may transmit a request to the receiver 16 requesting thatthe receiver 16 transmit a training signal set to the transmitter 12.Upon receiving the training signal set, the transmitter 12 may determinethe CSI for the reverse channel, and then determine a forward channelestimate based on the CSI for the reverse channel. The SNR for theforward channel may be determined based on the forward channel estimateor the CSI for the reverse channel (e.g., it may be assumed that the SNRfor the forward channel is the same as the SNR for the reverse channel).The training signal set, as discussed above, may include informationsufficient for determining the CSI for the channel. For a MIMO channelcorresponding to m receive antennas and n transmit antennas, the CSI maybe a full-dimensional description of the channel (i.e., providing anm-by-n description of the channel), or a partial-dimensional descriptionof the channel (i.e., providing a p-by-q description of the channel,where p<m and/or q<n). The training signal set may be included in apacket such as a sounding packet, a null data packet, etc. A request fora training signal set may be included in a packet.

At block 258, it may be determined if the SNR meets a criterion. Forexample, it may be determined if the SNR is less than a threshold, isless than or equal to a threshold, etc. Meeting the criterion mayindicate that the CSI for the channel may be unreliable if determinedconventionally. If the criterion is met, a plurality of training signalsets may be transmitted. Each training signal set in the plurality oftraining signal sets may include information sufficient for determiningthe CSI for the channel. For example, in the case of explicitbeamforming and/or explicit channel estimation, the transmitter 12 mayretransmit the same training signal set one or more additional times. Inresponse to each transmitted training signal set, the receiver 16 maydetermine CSI and, optionally, calculate an individual channel estimatebased on the CSI. In some implementations, an individual channelestimate may be set to CSI corresponding to one of the transmittedtraining signal sets. Then, the CSI or individual channel estimate maybe transmitted back to the transmitter 12. Alternatively, the receiver16 may generate a refined channel estimate, as will be described below,based on the CSI or individual channel estimates associated with theplurality of training signal sets. Then, the refined channel estimate(or a beamsteering matrix, for example, calculated based on the refinedchannel estimate) may be transmitted back to the transmitter 12. In thecase of implicit beamforming and/or implicit channel estimation, thetransmitter 12 may transmit one or more requests to the receiver 16requesting that the receiver 16 transmit one or more additional trainingsignal sets to the transmitter 12. A single request transmitted by thetransmitter 12 may be a request to transmit a single training signal setor a request to transmit a plurality of training signal sets. Thus,requesting that a plurality of transmit signal sets be transmitted mayinclude transmitting one or more packets, for example. In response toeach request, the receiver 16 may transmit a single training signal setor a plurality of training sets, depending on the type of request. Uponreceiving each training signal set, the transmitter 12 may determine CSIand calculate an individual channel estimate based on the CSI.

At block 262, a refined channel estimate may be calculated based on theplurality of training signal sets transmitted in connection with blocks254 and 258. In one implementation, an individual channel estimate maybe determined or calculated based on each transmitted training signalset. In this implementation, the refined channel estimate may becalculated based on the plurality of individual channel estimates. Forexample, the channel estimate may be calculated as a weightedcombination of the individual channel estimates:

$\begin{matrix}{{\hat{H}}_{{refined},p} = {\sum\limits_{j = 1}^{p}{w_{j,p}{\hat{H}}_{j}}}} & \left( {{Equation}\mspace{14mu} 1} \right)\end{matrix}$

where Ĥ_(refined,p) is the channel estimate after receiving the p-thtraining signal set, where Ĥ_(j) is the j-th individual channel estimatecorresponding to the j-th received training signal set, w_(j,p) is aweight to be applied to the j-th individual channel estimate. As can beseen with reference to above example, in contrast to conventionalmethods in which each channel estimate is calculated based on CSIcorresponding to only a single training signal set, a channel estimateis calculated based on CSI corresponding to a plurality of trainingsignal sets.

The weights w_(j,p) may be chosen according to any of a variety tosuitable weighting strategies. For example, uniform weighting may beutilized, where all of the p weights w_(j,p) are set to a same value,such as 1/p. This may be a suitable weighting strategy when theplurality of training signal sets are spaced relatively closely in timeand the channel varies slowly in time. As another example, the mostrecent individual channel estimate may be weighted most heavily, and theweights may decrease (e.g., linearly) as the individual channelestimates become less recent. For instance, the weights may be setaccording to:

$\begin{matrix}{w_{j,p} = \frac{2j}{p\left( {p + 1} \right)}} & \left( {{Equation}\mspace{14mu} 2} \right)\end{matrix}$Such a weighting strategy may be suitable for situations in which thetraining signal sets are spaced less closely, relatively, in time andthe channel varies more quickly in time. Many other weighting strategiesmay be used such as weights that vary non-linearly.

In one implementation, the refined channel estimate may be calculatedonly after all p training signal sets have been received or after theCSI for all p training signal sets have been received. For example, CSIcorresponding to each training signal set may be determined and storedin a memory as each training signal set is received. Then, after thep-th training signal set is received, the p individual channel estimatesmay be calculated based on the CSI's stored in the memory. Optionally,each individual channel estimate may be determined as CSI correspondingto a respective one of the plurality of training signal sets. In thisimplementation, a separate step of calculating individual channelestimates is not needed as the individual channel estimates are merelythe CSI. Next, the refined channel estimate may be calculated accordingto Equation 1, for example. Alternatively, the individual channelestimate corresponding to each training signal set may be determined orcalculated and stored in a memory as each training signal set isreceived. Then, after the p-th training signal set is received, therefined channel estimate may be calculated according to Equation 1, forexample.

In another implementation, the refined channel estimate may beiteratively calculated as each of the p training signal sets is receivedor as each of the CSI or individual channel estimates is received ordetermined. For example, as each training signal set is received, anindividual channel estimate may be determined or calculated. Then, theindividual channel estimate may be weighted and added to a sum of theprevious weighted individual channel estimates.

As another example, the refined channel estimate may be calculatedaccording to:Ĥ _(refined,p) =aĤ _(refined,p-1) +bĤ _(p)  (Equation 3)where a and b are weights that may be selected using a variety oftechniques. The iterative calculation of Equation 3 optionally may bestopped after p individual channel estimates have been processed.

At block 266, the refined channel estimate calculated at block 262 maybe utilized. For example, a steering matrix may be calculated using therefined channel estimate. As another example, a modulation coding set(MCS) may be selected based on the refined channel estimate. As anotherexample, the refined channel estimate may be utilized for determining anequalizer or for performing other processing at a transmitter orreceiver.

In one example, the refined channel estimate may be utilized (e.g., forbeamsteering calculation, MCS selection, equalizer calculation, etc.)only after the p-th training signal set has been received and therefined channel estimate has been determined based on all p individualchannel estimates. In another implementation, the refined channelestimate may be utilized (e.g., for beamsteering calculation, MCSselection, equalizer calculation, etc.) before the p-th training signalset has been received. For example, if the refined channel estimate isdetermined iteratively as each individual channel estimate is available,one or more versions of the refined channel estimate may be utilizedprior to processing all p individual channel estimates.

Optionally, a receiver may generate a refined channel estimate, asdescribed above, for a forward channel and then transmit the refinedchannel estimate for the forward channel back to the transmitter.

To improve reliability of reception, a training signal set may betransmitted without accompanying data (e.g., data included in the samepacket as the training signal set). For instance, the IEEE 802.11nStandard specifies a Null Data Packet (NDP) procedure. For devices to beutilized in IEEE 802.11n compliant systems, the NDP procedure may beutilized to transmit the plurality of training signal sets.

If the training signal set is transmitted with accompanying data, theaccompanying data may be transmitted according to a most reliable (orlowest) modulation coding set in order to improve reliability ofreception. Similarly, a CSI or individual channel estimate or refinedchannel estimate feedback signal (i.e., a signal providing the CSI orindividual channel estimate determined based on a transmitted trainingsignal set or a refined channel estimate determined based on a pluralityof training signal sets) may be transmitted according to a most reliable(or lowest) modulation coding set in order to improve reliability ofreception.

The IEEE 802.11n Standard specifies an antenna selection (ASEL)procedure that involves transmitting multiple sounding signals. Fordevices to be utilized in IEEE 802.11n compliant systems, the ASELprocedure may be exploited to transmit the plurality of training signalsets. Optionally, utilization of the ASEL procedure may be combined withthe NDP procedure.

If the method 250 is implemented in the system 10 of FIG. 1, blocks 254and 258 may be implemented, at least partially, by the controller 20 orthe controller 40, for example. Block 258 may be implemented, at leastpartially, by the channel determination unit 27 or the channeldetermination unit 39, for example. Block 262 may be implemented, atleast partially, by the steering matrix calculation unit 28, thesteering matrix calculation unit 48, the controller 20 or the controller40, the matrix equalizer 25, or the matrix equalizer 35, for example.

At least portions of the channel estimate techniques described hereinmay be implemented in software stored in, for example, one of thememories 21, 41 and implemented on a processor associated with one orboth of the controllers 20, 40, the steering matrix calculation units28, 48 and/or the channel determination units 27 and 39 of the MIMOcommunication system 10 of FIG. 1, or implanted in firmware as desired.If implemented in software, the routines may be stored in any computerreadable memory such as in RAM, ROM, flash memory, a magnetic disk, alaser disk, or other storage medium. Likewise, this software may bedelivered to a MIMO system device (such as a transmitter or a receiver)via any known or desired delivery method including, for example, over acommunication channel such as a telephone line, the Internet, a wirelessconnection, etc., or via a transportable medium, such as acomputer-readable disk, flash drive, etc.

More generally, the various blocks, operations, and techniques describedabove may be implemented in hardware, firmware, software, or anycombination of hardware, firmware, and/or software. When implemented inhardware, some or all of the blocks, operations, techniques, etc. may beimplemented in, for example, a custom integrated circuit (IC), anapplication specific integrated circuit (ASIC), a field programmablelogic array (FPGA), a programmable logic array (PLA), etc.

When implemented in software, the software may be stored in any computerreadable memory such as on a magnetic disk, an optical disk, or otherstorage medium, in a RAM or ROM or flash memory of a computer,processor, hard disk drive, optical disk drive, tape drive, etc.Likewise, the software may be delivered to a user or a system via anyknown or desired delivery method including, for example, on a computerreadable disk or other transportable computer storage mechanism or viacommunication media. Communication media typically embodies computerreadable instructions, data structures, program modules or other data ina modulated data signal such as a carrier wave or other transportmechanism. The term “modulated data signal” means a signal that has oneor more of its characteristics set or changed in such a manner as toencode information in the signal. By way of example, and not limitation,communication media includes wired media such as a wired network ordirect-wired connection, and wireless media such as acoustic, radiofrequency, infrared and other wireless media. Thus, the software may bedelivered to a user or a system via a communication channel such as awireless communication channel, a wired telephone line, a DSL line, acable television line, the Internet, etc. (which are viewed as being thesame as or interchangeable with providing such software via atransportable storage medium).

The present invention may be embodied in any type of wirelesscommunication system including, for example, ones used in wirelesscomputer systems such as those implemented via a local area network or awide area network, internet, cable and satellite based communicationsystems (such as internet, data, video and voice communication systems),wireless telephone systems (including cellular phone systems, voice overinternet protocol (VoIP) systems, home-based wireless telephone systems,etc.) Referring now to FIGS. 5A-5F, various example devices that mayembody the present invention are shown.

Referring now to FIG. 5A, channel estimation techniques such asdescribed above may be utilized in a high definition television (HDTV)1020. HDTV 1020 includes a mass data storage 1027, an HDTV signalprocessing and control block 1022, a WLAN interface and memory 1028.HDTV 1020 receives HDTV input signals in either a wired or wirelessformat and generates HDTV output signals for a display 1026. In someimplementations, signal processing circuit and/or control circuit 1022and/or other circuits (not shown) of HDTV 1020 may process data, performcoding and/or encryption, perform calculations, format data and/orperform any other type of HDTV processing that may be required.

HDTV 1020 may communicate with a mass data storage 1027 that stores datain a nonvolatile manner such as optical and/or magnetic storage devices.The mass storage device may be a mini HDD that includes one or moreplatters having a diameter that is smaller than approximately 1.8″. HDTV1020 may be connected to memory 1028 such as RAM, ROM, low latencynonvolatile memory such as flash memory and/or other suitable electronicdata storage. HDTV 1020 also may support connections with a WLAN via aWLAN network interface 1029. The WLAN network interface 1029 mayimplement channel estimation techniques such as described above.

Referring now to FIG. 5B, such techniques may be utilized in a vehicle1030. The vehicle 1030 includes a control system that may include massdata storage 1046, as well as a WLAN interface 1048. The mass datastorage 1046 may support a powertrain control system 1032 that receivesinputs from one or more sensors 1036 such as temperature sensors,pressure sensors, rotational sensors, airflow sensors and/or any othersuitable sensors and/or that generates one or more output controlsignals 1038 such as engine operating parameters, transmission operatingparameters, and/or other control signals.

Control system 1040 may likewise receive signals from input sensors 1042and/or output control signals to one or more output devices 1044. Insome implementations, control system 1040 may be part of an anti-lockbraking system (ABS), a navigation system, a telematics system, avehicle telematics system, a lane departure system, an adaptive cruisecontrol system, a vehicle entertainment system such as a stereo, DVD,compact disc and the like.

Powertrain control system 1032 may communicate with mass data storage1027 that stores data in a nonvolatile manner such as optical and/ormagnetic storage devices. The mass storage device 1046 may be a mini HDDthat includes one or more platters having a diameter that is smallerthan approximately 1.8″. Powertrain control system 1032 may be connectedto memory 1047 such as RAM, ROM, low latency nonvolatile memory such asflash memory and/or other suitable electronic data storage. Powertraincontrol system 1032 also may support connections with a WLAN via a WLANnetwork interface 1048. The control system 1040 may also include massdata storage, memory and/or a WLAN interface (all not shown). In oneexemplary embodiment, the WLAN network interface 1048 may implementchannel estimation techniques such as described above.

Referring now to FIG. 5C, such techniques may be used in a mobile phone1050 that may include a cellular antenna 1051. The mobile phone 1050 mayinclude either or both signal processing and/or control circuits, whichare generally identified in FIG. 5C at 1052, a WLAN network interface1068 and/or mass data storage 1064 of the cellular phone 1050. In someimplementations, mobile phone 1050 includes a microphone 1056, an audiooutput 1058 such as a speaker and/or audio output jack, a display 1060and/or an input device 1062 such as a keypad, pointing device, voiceactuation and/or other input device. Signal processing and/or controlcircuits 1052 and/or other circuits (not shown) in cellular phone 1050may process data, perform coding and/or encryption, performcalculations, format data and/or perform other mobile phone functions.

Mobile phone 1050 may communicate with mass data storage 1064 thatstores data in a nonvolatile manner such as optical and/or magneticstorage devices for example hard disk drives HDD and/or DVDs. The HDDmay be a mini HDD that includes one or more platters having a diameterthat is smaller than approximately 1.8″. Mobile phone 1050 may beconnected to memory 1066 such as RAM, ROM, low latency nonvolatilememory such as flash memory and/or other suitable electronic datastorage. Mobile phone 1050 also may support connections with a WLAN viaa WLAN network interface 1068. The WLAN network interface 1068 mayimplement channel estimation techniques such as described above.

Referring now to FIG. 5D, such techniques may be utilized in a set topbox 1080. The set top box 1080 may include either or both signalprocessing and/or control circuits, which are generally identified inFIG. 5D at 1084, a WLAN interface and/or mass data storage 1090 of theset top box 1080. Set top box 1080 receives signals from a source suchas a broadband source and outputs standard and/or high definitionaudio/video signals suitable for a display 1088 such as a televisionand/or monitor and/or other video and/or audio output devices. Signalprocessing and/or control circuits 1084 and/or other circuits (notshown) of the set top box 1080 may process data, perform coding and/orencryption, perform calculations, format data and/or perform any otherset top box function.

Set top box 1080 may communicate with mass data storage 1090 that storesdata in a nonvolatile manner and may use jitter measurement. Mass datastorage 1090 may include optical and/or magnetic storage devices forexample hard disk drives HDD and/or DVDs. The HDD may be a mini HDD thatincludes one or more platters having a diameter that is smaller thanapproximately 1.8″. Set top box 1080 may be connected to memory 1094such as RAM, ROM, low latency nonvolatile memory such as flash memoryand/or other suitable electronic data storage. Set top box 1080 also maysupport connections with a WLAN via a WLAN network interface 1096. TheWLAN network interface 1096 may implement channel estimation techniquessuch as described above.

Referring now to FIG. 5E, such techniques may be used in a media player1100. The media player 1100 may include either or both signal processingand/or control circuits, which are generally identified in FIG. 5E at1104, a WLAN interface and/or mass data storage 1110 of the media player1100. In some implementations, media player 1100 includes a display 1107and/or a user input 1108 such as a keypad, touchpad and the like. Insome implementations, media player 1100 may employ a graphical userinterface (GUI) that typically employs menus, drop down menus, iconsand/or a point-and-click interface via display 1107 and/or user input1108. Media player 1100 further includes an audio output 1109 such as aspeaker and/or audio output jack. Signal processing and/or controlcircuits 1104 and/or other circuits (not shown) of media player 1100 mayprocess data, perform coding and/or encryption, perform calculations,format data and/or perform any other media player function.

Media player 1100 may communicate with mass data storage 1110 thatstores data such as compressed audio and/or video content in anonvolatile manner and may utilize jitter measurement. In someimplementations, the compressed audio files include files that arecompliant with MP3 format or other suitable compressed audio and/orvideo formats. The mass data storage may include optical and/or magneticstorage devices for example hard disk drives HDD and/or DVDs. The HDDmay be a mini HDD that includes one or more platters having a diameterthat is smaller than approximately 1.8″. Media player 1100 may beconnected to memory 1114 such as RAM, ROM, low latency nonvolatilememory such as flash memory and/or other suitable electronic datastorage. Media player 1100 also may support connections with a WLAN viaa WLAN network interface 1116. The WLAN network interface 1116 mayimplement channel estimation techniques such as described above.

Referring to FIG. 5F, such techniques may be utilized in a Voice overInternet Protocol (VoIP) phone 1150 that may include an antenna 1152.The VoIP phone 1150 may include either or both signal processing and/orcontrol circuits, which are generally identified in FIG. 5F at 1154, awireless interface and/or mass data storage of the VoIP phone 1150. Insome implementations, VoIP phone 1150 includes, in part, a microphone1158, an audio output 1160 such as a speaker and/or audio output jack, adisplay monitor 1162, an input device 1164 such as a keypad, pointingdevice, voice actuation and/or other input devices, and a WirelessFidelity (WiFi) communication module 1166. Signal processing and/orcontrol circuits 1154 and/or other circuits (not shown) in VoIP phone1150 may process data, perform coding and/or encryption, performcalculations, format data and/or perform other VoIP phone functions.

VoIP phone 1150 may communicate with mass data storage 1156 that storesdata in a nonvolatile manner such as optical and/or magnetic storagedevices, for example hard disk drives HDD and/or DVDs. The HDD may be amini HDD that includes one or more platters having a diameter that issmaller than approximately 1.8″. VoIP phone 1150 may be connected tomemory 1157, which may be a RAM, ROM, low latency nonvolatile memorysuch as flash memory and/or other suitable electronic data storage. VoIPphone 1150 is configured to establish communications link with a VoIPnetwork (not shown) via WiFi communication module 1166. The WiFicommunication module 1166 may implement channel estimation techniquessuch as described above.

Moreover, while the present invention has been described with referenceto specific examples, which are intended to be illustrative only and notto be limiting of the invention, it will be apparent to those ofordinary skill in the art that changes, additions and/or deletions maybe made to the disclosed embodiments without departing from the spiritand scope of the invention.

What is claimed is:
 1. An apparatus comprising: a hardware deviceconfigured to generate a plurality of individual channel estimates basedon a plurality of received training signal sets received from a firstwireless transceiver, wherein each received training signal set includesinformation sufficient to determine a channel estimate corresponding toa first communication channel from the first wireless transceiver to asecond wireless transceiver, and determine a refined channel estimatebased on a mathematical combination of the plurality of individualchannel estimates.
 2. An apparatus according to claim 1, wherein therefined channel estimate is an estimate of a second communicationchannel from the second wireless transceiver to the first wirelesstransceiver, and wherein the hardware device is configured to:determine, based on the plurality of received training signal sets, anintermediate refined channel estimate of the first communicationchannel; and determine the estimate of the second communication channelbased on the intermediate refined channel estimate.
 3. An apparatusaccording to claim 1, wherein the hardware device is configured todetermine the refined channel estimate based on a weighted combinationof the plurality of individual channel estimates.
 4. An apparatusaccording to claim 3, wherein the hardware device is configured toweight the plurality of individual channel estimates with a plurality ofdifferent weights.
 5. An apparatus according to claim 1, wherein thehardware device is configured to determine the refined channel estimateiteratively after each received training signal set is received.
 6. Anapparatus according to claim 5, wherein the hardware device isconfigured to utilize, after each training signal set is received, theiteratively determined refined channel estimate to process a wirelesscommunication signal.
 7. An apparatus according to claim 1, wherein thehardware device is configured to utilize, only after the plurality ofreceived training signal sets has been received, the refined channelestimate to process a wireless communication signal.
 8. An apparatusaccording to claim 1, wherein the hardware device is configured to causea packet to be transmitted to the first wireless transceiver, whereinthe packet includes a request to transmit the plurality of trainingsignal sets.
 9. An apparatus according to claim 1, wherein the hardwaredevice is configured to cause a plurality of packets to be transmittedto the first wireless transceiver, wherein each packet in the pluralityof packets includes a request to transmit a respective one of theplurality of training signal sets.
 10. An apparatus according to claim1, wherein the hardware device is configured to cause the refinedchannel estimate to be transmitted to the first wireless transceiver.11. An apparatus according to claim 1, wherein the hardware device isconfigured to utilize the refined channel estimate to perform at leastone of (i) beamsteering or (ii) selecting a modulation and coding schemefor transmitting a signal.
 12. An apparatus according to claim 11,wherein the hardware device is configured to utilize the refined channelestimate to perform equalization of a received signal.
 13. An apparatuscomprising: a hardware device configured to cause a plurality oftraining signal sets to be transmitted from a first wireless transceiverto a second wireless transceiver, wherein each training signal setincludes information sufficient to determine a channel estimatecorresponding to a communication channel from the first wirelesstransceiver to the second wireless transceiver; and generate a refinedchannel estimate based on a mathematical combination of a plurality ofrespective individual channel estimates received from the secondwireless transceiver in response to each of the plurality of trainingsignal sets.
 14. An apparatus according to claim 13, wherein thehardware device is configured to determine the refined channel estimatebased on a weighted combination of the plurality of individual channelestimates.
 15. An apparatus according to claim 14, wherein the hardwaredevice is configured to weight the plurality of individual channelestimates with a plurality of different weights.
 16. An apparatusaccording to claim 13, wherein the hardware device is configured todetermine the refined channel estimate iteratively after each individualchannel estimate is received.
 17. An apparatus according to claim 16,wherein the hardware device is configured to utilize, after eachindividual channel estimate is received, the iteratively determinedrefined channel estimate to process a wireless communication signal. 18.An apparatus according to claim 13, wherein the hardware device isconfigured to utilize, only after the plurality of individual channelestimates has been received, the refined channel estimate to process awireless communication signal.
 19. An apparatus according to claim 13,wherein the hardware device is configured to determine a signal-to-noiseratio (SNR) associated with the communication channel, and cause theplurality of training signal sets to be transmitted only if it isdetermined that the SNR meets a criterion.
 20. An apparatus according toclaim 13, wherein the hardware device is configured to utilize therefined channel estimate to perform at least one of (i) beamsteering or(ii) selecting a modulation and coding scheme for transmitting a signal.